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自适应VMD的地震资料高分辨率处理方法研究

段成祥 梁圆 范晓辉 张繁昌 吴俊

段成祥, 梁圆, 范晓辉, 等. 自适应VMD的地震资料高分辨率处理方法研究[J]. CT理论与应用研究, 2022, 31(2): 135-148. DOI: 10.15953/j.1004-4140.2022.31.02.01
引用本文: 段成祥, 梁圆, 范晓辉, 等. 自适应VMD的地震资料高分辨率处理方法研究[J]. CT理论与应用研究, 2022, 31(2): 135-148. DOI: 10.15953/j.1004-4140.2022.31.02.01
DUAN C X, LIANG Y, FAN X H, et al. Research on high resolution seismic date processing method based on adaptive VMD[J]. CT Theory and Applications, 2022, 31(2): 135-148. DOI: 10.15953/j.1004-4140.2022.31.02.01. (in Chinese)
Citation: DUAN C X, LIANG Y, FAN X H, et al. Research on high resolution seismic date processing method based on adaptive VMD[J]. CT Theory and Applications, 2022, 31(2): 135-148. DOI: 10.15953/j.1004-4140.2022.31.02.01. (in Chinese)

自适应VMD的地震资料高分辨率处理方法研究

doi: 10.15953/j.1004-4140.2022.31.02.01
基金项目: 国家自然科学基金面上项目(致密裂隙介质波致流机理及物性甜点检测关键算法研究(41874146))
详细信息
    作者简介:

    段成祥:男,中国石油大学(华东)地质工程专业硕士研究生,主要从事地震资料处理及解释研究,E-mail:duancx2021@126.com

  • 中图分类号: P  315;P  631;O  242

Research on High Resolution Seismic Date Processing Method Based on Adaptive VMD

  • 摘要: 随着勘探开发的不断深入,常规地震资料受分辨率的限制难以满足精细勘探开发的需求。由于地震信号不同频率成分的衰减程度不同,故可结合分频技术对各频率成分进行差异化补偿,进而提高地震资料分辨率。而常规分频技术普遍分频精度不高,存在模态混叠现象,不能较好地适用于地震资料处理。针对上述问题,本文提出基于自适应变分模态分解(VMD)的地震资料高分辨率处理方法。将多目标蝙蝠算法应用于变分模态分解,利用功率谱熵、能量差、样本熵构建适应度函数,对VMD参数进行优化。模型测试结果表明,优化的VMD方法分频精度较高,避免模态混叠,且具有较强的抗噪能力;将优化VMD方法应用于地震资料高分辨率处理,模型及实际数据测试结果表明,处理后的地震资料分辨率得到有效提高。

     

  • 图  1  合成信号及频谱图

    Figure  1.  Synthetic signal and amplitude spectrum

    图  2  适应度值随迭代次数变化曲线

    Figure  2.  Curve of fitness value with the number of iterations

    图  3  信号$ y $的VMD分解及重构结果

    Figure  3.  VMD decomposition and reconstruction results of signaly

    图  4  合成地震记录

    Figure  4.  Synthetic seismic record

    图  5  经VMD高频补偿前后信号对比

    Figure  5.  Signal comparison before and after VMD high frequency compensation

    图  6  经VMD高频补偿前后信号振幅谱对比

    Figure  6.  Comparison of signal amplitude spectrum before and after VMD high frequency compensation

    图  7  原始地震数据

    Figure  7.  Original seismic data

    图  8  反褶积方法处理结果

    Figure  8.  Deconvolution processing result

    图  9  本文方法高频补偿后结果

    Figure  9.  The result of this method after high frequency compensation

    图  10  本方法处理前后频谱对比

    Figure  10.  Spectrum comparison before and after processing by this method

    表  1  优化VMD分解精度评价指标

    Table  1.   Optimize the evaluation index of VMD decomposition accuracy

    对应分量相关系数标准误差
    IMF1-y10.98040.1025
    IMF2-y20.98380.0904
    IMF3-y30.98310.1302
    Fig.3(i)-Fig.1(g)0.99510.0512
    下载: 导出CSV
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  • 收稿日期:  2021-01-07
  • 网络出版日期:  2022-01-25
  • 刊出日期:  2022-04-01

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